| 2007 |
| 18 | EE | Roberto Esposito,
Daniele P. Radicioni:
Trip Around the HMPerceptron Algorithm: Empirical Findings and Theoretical Tenets.
AI*IA 2007: 242-253 |
| 17 | EE | Daniele P. Radicioni,
Roberto Esposito:
Tonal Harmony Analysis: A Supervised Sequential Learning Approach.
AI*IA 2007: 638-649 |
| 16 | EE | Roberto Esposito,
Daniele P. Radicioni:
CarpeDiem: an algorithm for the fast evaluation of SSL classifiers.
ICML 2007: 257-264 |
| 15 | EE | Arianna Gallo,
Roberto Esposito,
Rosa Meo,
Marco Botta:
Incremental Extraction of Association Rules in Applicative Domains.
Applied Artificial Intelligence 21(4&5): 297-315 (2007) |
| 2006 |
| 14 | EE | Daniele P. Radicioni,
Roberto Esposito:
A Conditional Model for Tonal Analysis.
ISMIS 2006: 652-661 |
| 13 | EE | Roberto Esposito,
Rosa Meo,
Marco Botta:
Answering constraint-based mining queries on itemsets using previous materialized results.
J. Intell. Inf. Syst. 26(1): 95-111 (2006) |
| 2005 |
| 12 | EE | Arianna Gallo,
Roberto Esposito,
Rosa Meo,
Marco Botta:
Optimization of Association Rules Extraction Through Exploitation of Context Dependent Constraints.
AI*IA 2005: 258-269 |
| 11 | EE | Roberto Esposito,
Lorenza Saitta:
Experimental comparison between bagging and Monte Carlo ensemble classification.
ICML 2005: 209-216 |
| 2004 |
| 10 | EE | Rosa Meo,
Marco Botta,
Roberto Esposito,
Arianna Gallo:
A Novel Incremental Approach to Association Rules Mining in Inductive Databases.
Constraint-Based Mining and Inductive Databases 2004: 267-294 |
| 9 | EE | Rosa Meo,
Pier Luca Lanzi,
Maristella Matera,
Danilo Careggio,
Roberto Esposito:
Employing Inductive Databases in Concrete Applications.
Constraint-Based Mining and Inductive Databases 2004: 295-327 |
| 8 | | Roberto Esposito:
Empirical Evaluation of the Effects of Concept Complexity on Generalization Error.
ECAI 2004: 1009-1010 |
| 7 | EE | Rosa Meo,
Marco Botta,
Roberto Esposito:
Query Rewriting in Itemset Mining.
FQAS 2004: 111-124 |
| 6 | EE | Roberto Esposito,
Lorenza Saitta:
A Monte Carlo analysis of ensemble classification.
ICML 2004 |
| 5 | EE | Rosa Meo,
Pier Luca Lanzi,
Maristella Matera,
Roberto Esposito:
Integrating Web Conceptual Modeling and Web Usage Mining.
WebKDD 2004: 135-148 |
| 2003 |
| 4 | EE | Roberto Esposito,
Lorenza Saitta:
Explaining Bagging with Monte Carlo Theory.
AI*IA 2003: 189-200 |
| 3 | | Roberto Esposito,
Lorenza Saitta:
Monte Carlo Theory as an Explanation of Bagging and Boosting.
IJCAI 2003: 499-504 |
| 2002 |
| 2 | EE | Roberto Esposito,
Lorenza Saitta:
Is a Greedy Covering Strategy an Extreme Boosting?
ISMIS 2002: 94-102 |
| 2001 |
| 1 | EE | Roberto Esposito,
Lorenza Saitta:
Boosting as a Monte Carlo Algorithm.
AI*IA 2001: 11-19 |